Open AccessMachine Learning for High Risk Pregnancies Pre-Term Birth Prediction: A Retrospective
Author(s) -
M. Ramla,
S. Sangeetha,
S. Nickolas
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.22.11799
Subject(s) - term (time) , estimation , focus (optics) , computer science , psychology , obstetrics , artificial intelligence , medicine , engineering , physics , quantum mechanics , systems engineering , optics
Any birth before 28 weeks of gestation is termed as Pre-Term. This has substantial impact in the emotional reactions of mothers. The post-traumatic stress notably in the mother could be of chronic psychological risk. Moreover, it is to be addressed in the global scenario for sustainable development. Predicting stillbirths is still a distant reality. A plethora of works have been carried out and this paper present the summaries and analysis of current research. The primary focus of the paper is to throw light on the challenging issue of Preterm Birth Prediction. Myriad of machine learning techniques are used by various researchers each with its own estimation accuracy and type of ML model.